Reference
K. Máthé, L. Buşoniu, R. Munos, and B. De Schutter,
"Optimistic planning with an adaptive number of action switches for
near-optimal nonlinear control,"
Engineering Applications of
Artificial Intelligence, vol. 67, pp. 355-367, 2018.
Abstract
We consider infinite-horizon optimal control of nonlinear systems where the
control actions are discrete, and focus on optimistic planning algorithms from
artificial intelligence, which can handle general nonlinear systems with
nonquadratic costs. With the main goal of reducing computations, we introduce
two such algorithms that only search for constrained action sequences. The
constraint prevents the sequences from switching between different actions more
than a limited number of times. We call the first method optimistic
switch-limited planning (OSP), and develop analysis showing that its fixed
number of switches S leads to polynomial complexity in the search horizon, in
contrast to the exponential complexity of the existing OP algorithm for
deterministic systems; and to a correspondingly faster convergence towards
optimality. Since tuning S is difficult, we introduce an adaptive variant
called OASP that automatically adjusts S so as to limit computations while
ensuring that near-optimal solutions keep being explored. OSP and OASP are
analytically evaluated in representative special cases, and numerically
illustrated in simulations of a rotational pendulum. To show that the
algorithms also work in challenging applications, OSP is used to control the
pendulum in real time, while OASP is applied for trajectory control of a
simulated quadrotor.
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BibTeX
@article{MatBus:17-017,
author = {M{\'{a}}th{\'{e}}, Kopp{\'{a}}ny and Bu{\c{s}}oniu, Lucian and
Munos, R{\'{e}}mi and De Schutter, Bart},
title = {Optimistic Planning with an Adaptive Number of Action Switches
for Near-Optimal Nonlinear Control},
journal = {Engineering Applications of Artificial Intelligence},
volume = {67},
pages = {355--367},
year = {2018}
}